Maintaining optimal cognitive performance is important relative to learning and productivity as well as avoiding industrial and motor vehicle accidents. Cognitive performance varies throughout the day thereby influencing the quality of performance, including how we use and interact with vehicles, devices, resources, and applications.
Cognitive performance decreases significantly after a loss of sleep. Understanding the real-world impact of sleep deficiency is critical. The estimated cost of fatigue to U.S. businesses exceeds $150 billion a year in absenteeism, workplace accidents, poor and delayed decision-making and other lost productivity on top of the increased health care costs and risk of disease. Despite the importance sleep-related performance, temporal variations of real-world performance based on sleep are not well understood and have never been characterized on a large scale.
Cognitive performance varies throughout each day and is driven in part by intrinsic, near 24-hour circadian rhythms. Existing research on the impact of sleep and circadian rhythms on cognitive performance has typically been restricted to small-scale laboratory-based studies that do not capture the variability of real-world conditions, such as environmental factors, motivation, and sleep patterns in real-world settings.
Daily patterns in human cognitive performance are typically modeled based on representations of three biological processes: (i) circulation rhythms (time-dependent, behavior-independent, near 24-hour oscillations); (ii) homeostatic sleep pressure (the longer awake, the more tired you become); and (iii) sleep inertia (performance impairment experienced immediately after waking up).
Existing sleep-related correlations are typically based on experimental studies in which participants are deprived of sleep and undertake regular, artificial tasks to measure performance instead of non-intrusively capturing performance through everyday tasks in real-world environments. In addition, the participants in an artificial laboratory setting can be influenced by their understanding of the study and subconsciously change their behavior.
Laboratory studies usually fail to account for a myriad of influences in the real-world, including motivation, mood, illness, environmental conditions, behavioral compensation including caffeine intake, and sleep patterns in the wild that are far more complicated than those enforced in research studies. In contrast, real-world cognitive performance varies throughout the day and is influenced by both circadian rhythms, chronotypes (morning/evening preference), and prior sleep duration and timing.